The invention pertains to machine vision and, more particularly, to methods for determining characteristics of an object represented in an image. The invention has application inter alia in the machine inspection of back-lit objects, such as semiconductor chip surface mounted devices.
Machine vision refers to the automated analysis of an image to determine characteristics of objects and other features shown therein. It is often employed in automated manufacturing lines, where images of components are analyzed to determine placement and alignment prior to assembly. Machine vision is also used for quality assurance. For example, in the pharmaceutical and food packing industries, images of packages are analyzed to insure that product labels, lot numbers, "freshness" dates, and the like, are properly positioned and legible.
In many machine vision applications, it is often essential to identify the boundaries of objects in images. In the semiconductor industry, for example, semiconductor chip surface mounted devices (SMDs) must be precisely positioned and oriented before they can be soldered into place on a printed circuit board. Typically, those components are "back-lit," i.e., illuminated from behind such that images of only their silhouettes are presented for machine vision analysis.
The machine vision analysis of back-lit SMDs can be difficult because the visual features (e.g., edge points) presented in their images must be matched to internal models of the components. This is necessary to permit determination of accurate transformations from model to physical coordinates (i.e., the physical position of the SMD). The process must be fast, moreover, so that an automated surface mounter can inspect and place each device on the board quickly. It must also be accurate enough to insure that chip leads substantialy contact pads on the board.
This problem may be complicated further by extraneous structures in the images. Like other delicate electronic components, SMDs are typically manipulated during assembly by suction nozzles. These small vacuum tips are used to pick the chips out of bins, present them for inspection to the machine vision camera, and place them on boards. Although the nozzles are usually arranged to pick up the SMDs from behind, they sometimes cast shadows or protrude beyond the edges of the chips, resulting in silhouettes that interfere with determination of chip location, orientation and other characteristics.
Other complications arise from the lighting conditions. Often, back-lighting will cause the otherwise rectangular chips to appear as if they have rounded comers. Image features extracted around these comer points do not accurately reflect the physical structure of the chip and, hence, also confound inspection.
Still further, as with other manufactured devices, each SMD has a slightly different size and shape than the others. Although each chip must satisfy a set of manufacturing specifications, e.g., width and length tolerances, there is no guarantee that chip corners will be sharp, nor that edges be completely straight.
An object of this invention is to provide improved machine vision methods and, particularly, improved methods for determining characteristics of an object in an image.
A further object is to provide such methods as permit the rapid determination of characteristics, such as dimensions, position, and orientation, of rectilinear and other polygonal objects.
Still another object is to provide such methods as can be adapted for use in analyzing images of back-lit objects.
Yet still another object is to provide such methods as can be readily implemented on conventional digital data processors or other conventional machine vision analysis equipment.
Yet still another object of the invention is to provide such methods that can rapidly analyze images without undue consumption of computational resources.